As we continue our journey through the differences between sales forecasting, CRM and sales analytics applications, we need to consider not only how they foster collaboration between the participants in the forecasting process, but how they can make the forecasting process most effective.
Difference #3: How these systems build a complete sales forecast that maximizes forecasting effectiveness
The core challenge of sales forecasting is to maximize insight into key drivers of the business while at the same time not making the forecasting process too onerous to sales people, product managers and executives. A process that is too “heavy” will kill productivity for the participants while a process that is too “light” will not provide adequate visibility into where the business is going. If a sales forecasting process is too time consuming or complex, adoption is negatively impacted. If forecasting adoption is low, the company will not have the data to find the insights it is looking for. The most effective forecast is one that minimizes effort while maximizing results. How do our three favorite systems minimize the forecasting effort while maximizing effectiveness?
A Sales Forecasting System offers a suite of tools and best practice templates to assist customers in designing a sales forecasting process that balances the need for complete information with the importance of minimizing the time spent forecasting. A sales forecasting system enables all the constituents that build the forecast (sales, sales ops, sales management, marketing, operations, finance) to use the same tool. The game can be played by all with the same bat and ball. A sales forecasting system supports key capabilities like:
- multiple plans (revenue, product, regional)
- customer tiering
- statistical forecasting baselines for standard or high volume parts
- plug values for buckets of small customers and partners
- analytics to uncover insights, and more.
All of these capabilities help companies minimize the time required to create a complete sales forecast and derive actionable insights. This maximizes the effectiveness of the sales forecasting process.
A CRM System is focused on minimizing the time a sales rep spends managing their opportunities. Sales ops often fills the gap between new business and run rate business with spreadsheets. Also, CRM does not provide native support for multiple plans, statistical tool integration, forecasting best practices, or other key sales forecasting requirements. If companies want these capabilities they need to integrate third party applications, or develop these capabilities themselves. This often adds complexity to the sales forecast process and decreases the quantity and quality of insights a company can obtain.
As mentioned before, a Sales Analytics System does not have independent data capture capabilities, instead sales analytics rely solely upon the data contained in the CRM system to derive insights. This limited view of opportunities does not help companies much in building the sales forecast and delivers minimal forecasting effectiveness.
Combining CRM and Sales Analytics yields a good way for sales to manage new opportunities, yet leaves the other ball players, and much of the game, off the field.
Having the right application helps companies build a complete forecast of new and recurring revenue with minimal effort from all the players. It also delivers maximum value through actionable insights. Next we’ll discuss how companies get these actionable insights. It starts with assessing the quality and reliability of the forecast.
Tags: enterprise sales forecast, sales analytics, sales forecasting